Weekly maintenance every saturday 03:00 - 06:00 UTC

- Mean historical return.

- Exponentially weighted mean historical return.

- CAPM estimate of returns.

- Fix non-positive semidefinite matrices.

- Sample covariance.

- Semicovariance.

- Exponentially weighted covariance.

- Shrunk covariance matrices:

- manual shrinkage

- Ledoit Wolf shrinkage

- Oracle Approximating shrinkage

Mean-Variance optimization.

- minimum of volatility

- maximum of Sharpe ratio

- maximum of the quadratic utility, given some risk aversion

- maximum of return for a given target risk

- minimum of risk for a given target return

Semivariance optimization.

- minimum of semivariance

- maximum of the quadratic utility, given some risk aversion

- maximum of return for a given target risk

CVaR and CDaR optimization.

- minimum of CVaR or CDaR

- maximum of return for a given CVaR or CDaR

- minimum of CVaR or CDaR for a given target return

- All of these methods support **L2 regularization** also.

To start the portfolio optimization refer to the Quickstart page.

If you have a questions or bug reports, feel free to contact me either with contact email or redirecting by the link "Ask a question", which is located on the left sidebar (but you should register on github for this).